Intra-rater repeatability of gait parameters in healthy adults during self-paced treadmill-based virtual reality walking

Self-paced treadmill walking is becoming increasingly popular for the gait assessment and re-education, in both research and clinical settings. Its day-to-day repeatability is yet to be established. This study scrutinised the test-retest repeatability of key gait parameters, obtained from the Gait Real-time Analysis Interactive Lab (GRAIL) system. Twenty-three male able-bodied adults (age: 34.56 ± 5.12 years) completed two separate gait assessments on the GRAIL system, separated by 5 ± 3 days. Key gait kinematic, kinetic, and spatial-temporal parameters were analysed. The Intraclass-Correlation Coefficients (ICC), Standard Error Measurement (SEM), Minimum Detectable Change (MDC), and the 95% limits of agreements were calculated to evaluate the repeatability of these gait parameters. Day-to-day agreements were excellent (ICCs > 0.87) for spatial-temporal parameters with low MDC and SEM values, <0.153 and <0.055, respectively. The repeatability was higher for joint kinetic than kinematic parameters, as reflected in small values of SEM (<0.13 Nm/kg and <3.4°) and MDC (<0.335 Nm/kg and <9.44°). The obtained values of all parameters fell within the 95% limits of agreement. Our findings demonstrate the repeatability of the GRAIL system available in our laboratory. The SEM and MDC values can be used to assist researchers and clinicians to distinguish ‘real’ changes in gait performance over time.     

A new parameter for quantifying the variability of surface electromyographic signals during gait: The occurrence frequency

Natural variability of myoelectric activity during walking was recently analyzed considering hundreds of strides. This allowed assessing a parameter seldom considered in classic surface EMG (sEMG) studies: the occurrence frequency, defined as the frequency each muscle activation occurs with, quantified by the number of strides when a muscle is recruited with that specific activation modality. Aim of present study was to propose the occurrence frequency as a new parameter for assessing sEMG-signal variability during walking. Aim was addressed by processing sEMG signals acquired from Gastrocnemius Lateralis, Tibialis Anterior, Rectus Femoris and Biceps femoris in 40 healthy subjects in order to: (1) show that occurrence frequency is not correlated with ON/OFF instants (R_mean = 0.11 ± 0.07; P > 0.05) and total time of activation (R_mean = 0.15 ± 0.08; P > 0.05); (2) confirm the above results by two handy examples of application (analysis of gender and age) which highlighted that significant (P < 0.05) gender-related and age-related differences within population were detected in occurrence frequency, but not in temporal sEMG parameters. In conclusion, present study demonstrated that occurrence frequency is able to provide further information, besides those supplied by classical temporal sEMG parameters and thus it is suitable to complement them in the evaluation of variability of myoelectric activity during walking.     

Functional Near Infrared Spectroscopy of the Sensory and Motor Brain Regions with Simultaneous Kinematic and EMG Monitoring During Motor Tasks

There are several advantages that functional near-infrared spectroscopy (fNIRS) presents in the study of the neural control of human movement. It is relatively flexible with respect to participant positioning and allows for some head movements during tasks. Additionally, it is inexpensive, light weight, and portable, with very few contraindications to its use. This presents a unique opportunity to study functional brain activity during motor tasks in individuals who are typically developing, as well as those with movement disorders, such as cerebral palsy. An additional consideration when studying movement disorders, however, is the quality of actual movements performed and the potential for additional, unintended movements. Therefore, concurrent monitoring of both blood flow changes in the brain and actual movements of the body during testing is required for appropriate interpretation of fNIRS results. Here, we show a protocol for the combination of fNIRS with muscle and kinematic monitoring during motor tasks. We explore gait, a unilateral multi-joint movement (cycling), and two unilateral single-joint movements (isolated ankle dorsiflexion, and isolated hand squeezing). The techniques presented can be useful in studying both typical and atypical motor control, and can be modified to investigate a broad range of tasks and scientific questions.     

MRI metrics at the epicenter of spinal cord injury are correlated with the stepping process in rhesus monkeys

Clinical evaluations of long-term outcomes in the early-stage spinal cord injury (SCI) focus on macroscopic motor performance and are limited in their prognostic precision. This study was designed to investigate the sensitivity of the magnetic resonance imaging (MRI) indexes to the data-driven gait process after SCI. Ten adult female rhesus monkeys were subjected to thoracic SCI. Kinematics-based gait examinations were performed at 1 (early stage) and 12 (chronic stage) months post-SCI. The proportion of stepping (PS) and gait stability (GS) were calculated as the outcome measures. MRI metrics, which were derived from structural imaging (spinal cord cross-sectional area, SCA) and diffusion tensor imaging (fractional anisotropy, FA; axial diffusivity, λ_//), were acquired in the early stage and compared with functional outcomes by using correlation analysis and stepwise multivariable linear regression. Residual tissue SCA at the injury epicenter and residual tissue FA/remote normal-like tissue FA were correlated with the early-stage PS and GS. The extent of lesion site λ_///residual tissue λ_// in the early stage after SCI was correlated with the chronic-stage GS. The ratios of lesion site λ_// to residual tissue λ_// and early-stage GS were predictive of the improvement in the PS at follow-up. Similarly, the ratios of lesion site λ_// to residual tissue λ_// and early-stage PS best predicted chronic GS recovery. Our findings demonstrate the predictive power of MRI combined with the early data-driven gait indexes for long-term outcomes. Such an approach may help clinicians to predict functional recovery accurately.     

Gyroscopic corrections improve wearable sensor data prior to measuring dynamic sway in the gait of people with Multiple Sclerosis

Accelerometers are incorporated into many consumer devices providing new ways to monitor gait, mobility, and fall risk. However, many health benefits have not been realised because of issues with data quality that results from gravitational ‘cross-talk’ when the wearable device is tilted. Here we present an adaptive filter designed to improve the quality of accelerometer data prior to measuring dynamic pelvic sway patterns during a six minute walk test in people with and without Multiple Sclerosis (MS). Optical motion capture was used as the gold standard. Improved wearable device accuracy (≤4.4% NRMSE) was achieved using gyroscopic corrections and scaling filter thresholds by step frequency. The people with MS presented significantly greater pelvis sway range to compensate for their lower limb weaknesses and joint contractures. The visualisation of asymmetric pelvic sway in people with MS illustrates the potential to better understand their mobility impairments for reducing fall risk.     

Low-grade chronic inflammation and superoxide anion production by NADPH oxidase are the main determinants of physical frailty in older adults

Abstract

Background. Physical performance measured by gait speed is being recognized as a major instrument for clinical evaluation in older adults, because it predicts physical frailty, loss of autonomy, hospitalization and decreased survival. Low-grade chronic inflammation and oxidative stress, mediated partly by the superoxide anion produced by NADPH oxidase, are closely linked and could be involved in age-related physical decline. Objective. To determine whether slow gait speed is associated with superoxide anion overproduction by NADPH oxidase and low-grade chronic inflammation. Design and setting. Observational study among the 280 elderly of an ambulatory geriatric care unit (191 women, 89 men, 79.9 ± 6.1 years old). Methods. Gait speed was evaluated by walking at self-chosen usual pace. Usual gait speed < 0.8 m/s was defined as slow gait speed. Superoxide anion production was evaluated using a lucigenin-based chemiluminescence method. Inflammation was evaluated by CRP, fibrinogen and leukocyte count. Results. Among the 280 participants, 179 (63.9%) walked with a gait speed < 0.8 m/s (slow walkers) and 101 (36.1%) with a gait speed ≥ 0.8 m/s. Superoxide production and inflammation markers, such as fibrinogen, were more important in slow walkers (p = 0.004 and p = 0.006, respectively). In multivariate analysis, superoxide anion overproduction and fibrinogen were independently associated with physical frailty assessed by slow gait speed (p = 0.028 and p = 0.007, respectively). Conclusion. Physical frailty in older people is associated with superoxide anion overproduction by NADPH oxidase and low-grade chronic inflammation.     

Prediction of ground reaction forces during gait based on kinematics and a neural network model

Kinetic information during human gait can be estimated with inverse dynamics, which is based on anthropometric, kinematic, and ground reaction data. While collecting ground reaction data with a force plate is useful, it is costly and requires regulated space. The goal of this study was to propose a new, accurate methodology for predicting ground reaction forces (GRFs) during level walking without the help of a force plate. To predict GRFs without a force plate, the traditional method of Newtonian mechanics was used for the single support phase. In addition, an artificial neural network (ANN) model was applied for the double support phase to solve statically indeterminate structure problems. The input variables of the ANN model, which were selected to have both dependency and independency, were limited to the trajectory, velocity, and acceleration of the whole segment's mass centre to minimise errors. The predicted GRFs were validated with actual GRFs through a ten-fold cross-validation method, and the correlation coefficients (R) for the ground forces were 0.918 in the medial–lateral axis, 0.985 in the anterior–posterior axis, and 0.991 in the vertical axis during gait. The ground moments were 0.987 in the sagittal plane, 0.841 in the frontal plane, and 0.868 in the transverse plane during gait. The high correlation coefficients(R) are due to the improvement of the prediction rate in the double support phase. This study also proved the possibility of calculating joint forces and moments based on the GRFs predicted with the proposed new hybrid method. Data generated with the proposed method may thus be used instead of raw GRF data in gait analysis and in calculating joint dynamic data using inverse dynamics.     

Radial Glial Fibers Promote Neuronal Migration and Functional Recovery after Neonatal Brain Injury

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